class_docstr: Task for training masked language models (e.g., BERT, RoBERTa).
class_docstr_tok: ["Task","for","training","masked","language","models","(","e.g.",",","BERT",",","RoBERTa",")","."]
code: def __init__(self, args, dictionary):
      super().__init__(args)
      self.dictionary = dictionary
      self.seed = args.seed
  
      # add mask token
      self.mask_idx = dictionary.add_symbol("<mask>")
  
file_path: fairseq/fairseq/tasks/multilingual_masked_lm.py
imports: import logging
  import os
  import numpy
  import torch
  from fairseq import utils
  from fairseq.data import ConcatDataset, Dictionary, IdDataset, MaskTokensDataset, NestedDictionaryDataset, NumelDataset, NumSamplesDataset, PadDataset, PrependTokenDataset, RawLabelDataset, ResamplingDataset, SortDataset, TokenBlockDataset, data_utils, encoders
  from fairseq.tasks import LegacyFairseqTask, register_task
label_desc: Use image node_id 2 to create a new MultiLingualMaskedLMTask object from inherited base classes: LegacyFairseqTask with example: obj = MultiLingualMaskedLMTask(args, dictionary)